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Journal Article

Vesicle pool partitioning influences presynaptic diversity and weighting in rat hippocampal synapses


Waters,  David Jack
Department of Cell Physiology, Max Planck Institute for Medical Research, Max Planck Society;

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Waters, D. J., & Smith, S. J. (2002). Vesicle pool partitioning influences presynaptic diversity and weighting in rat hippocampal synapses. Journal of Physiology, 541(3), 811-823. doi:10.1113/jphysiol.2001.013485.

Cite as: http://hdl.handle.net/21.11116/0000-0001-EF7B-9
Hippocampal synapses display a range of release probabilities. This is partially the result of scaling of release probability with the total number of releasable vesicles at each synapse. We have compared synaptic release and vesicle pool sizes across a large number of hippocampal synapses using FM 1-43 and confocal fluorescence microscopy. We found that the relationship between the number of recycling vesicles at a synapse and its release probability is dependent on firing frequency. During firing at 10 Hz, the release probability of each synapse is closely related to the number of recycling vesicles that it contains. In contrast, during firing at 1 Hz, different synapses turn over their recycling vesicle pools at different rates leading to an indirect relationship between recycling vesicle pool size and release probability. Hence two synapses may release vesicles at markedly different rates during low frequency firing, even if they contain similar numbers of vesicles. Both further kinetic analyses and manipulation of the number of vesicles in the readily releasable pool using phorbol ester treatment suggested that this imprecise scaling observed during firing at 1 Hz resulted from synapse-to-synapse differences in the proportion of recycling vesicles partitioned into the readily releasable pool. Hence differential partitioning between vesicle pools affects presynaptic weighting in a frequency-dependent manner. Since hippocampal single unit firing rates shift between 1 Hz and 10 Hz regimes with behavioural state, differential partitioning may be a mechanism for encoding information in hippocampal circuits.